Airport and Ground Access Choice Modeling
Corresponding Author: Chrissy Bernardo, WSP
Presented By: Chrissy Bernardo, WSP
Airport planning and regional transportation planning are inherently intertwined. Airports are generators of thousands of trips with unique characteristics compared to other trip purposes (e.g. higher Value Of Time (VOT), higher vehicle occupancy/party size (for non-business travelers), greater impedance for walking or transferring between modes due to the luggage, differing trip lengths, etc.), that regional models need to account for in order to fully represent regional travel patterns. Airports also represent major employment centers that must be properly accounted for in regional commuting patterns.
In this paper, the regional model and an airport ground access model have been brought together in a framework designed for the New York Metropolitan area. Nine regional airports and eight access modes form the joint set of 72 alternatives in the airport and ground access mode choice model. The access mode level of service characteristics are derived from the regional travel demand model (and can be modified to test potential scenarios, such as new transit service). In turn, the results of the airport choice model are used to feed special generator information in the regional model.
The airport and ground access mode choice model utilizes a novel approach to the incremental logit model, which the authors have termed a “switching” logit model application. The switching model is applied in a sample enumeration framework, comparing the utilities of all alternative choices to the alternative that was actually chosen by each individual in the original sample. This model was used for scenario analysis for the Port Authority of New York and New Jersey’s Airport Capacity Planning Study, and was adapted for use in forecasting JFK AirTrain ridership. For the AirTrain ridership study, the model was modified to predict detailed ridership on different segments of the AirTrain line, rather than total passenger levels at different regional airports, through an additional segmentation of riders and special multi-dimensional weighting procedures. The model also was used to test AirTrain fare sensitivity while accounting for planned toll and transit fare increases on regional transportation systems.